What is the Point of Change? Change Point Detection in Relational Event Models

Mahdi Shafiee Kamalabad; Roger Leenders; Joris Mulder

doi:10.1016/j.socnet.2023.03.004

What is the Point of Change? Change Point Detection in Relational Event Models

Mahdi Shafiee Kamalabad^*, Roger Leenders, Joris Mulder

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

This paper presents an extension to the relational event model with change points (REM-CP) to study abrupt changes to social interaction behavior in temporal networks. A change point detection algorithm is proposed for exploring when and which network effects abruptly change, and a confirmatory approach to test the presence of a change point at a given moment. The effectiveness of the methodology was assessed with numerical simulations and NASA's Apollo 13 mission data. The latter revealed dynamic communication behavior and identified time zones where most change points occurred, including around the time of the famous quote “Houston, we've had a problem.”

Original language	English
Pages (from-to)	166-181
Number of pages	16
Journal	Social Networks
Volume	74
DOIs	https://doi.org/10.1016/j.socnet.2023.03.004
Publication status	Published - Jul 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Funding

The authors wish to thank the review team for their feedback which resulted in important improvements of the manuscript. This work was supported by an ERC Starting Grant ( 758791 ).

Funders	Funder number
European Research Council	758791

Keywords

Bayes factor
Change point detection
Communication
Critical incident analysis
Critical situation
Graceful extensibility
Relational event model
Resilience engineering
Social network analysis

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10.1016/j.socnet.2023.03.004Licence: CC BY

1-s2.0-S0378873323000254-mainFinal published version, 11.9 MBLicence: CC BY

Cite this

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title = "What is the Point of Change? Change Point Detection in Relational Event Models",

abstract = "This paper presents an extension to the relational event model with change points (REM-CP) to study abrupt changes to social interaction behavior in temporal networks. A change point detection algorithm is proposed for exploring when and which network effects abruptly change, and a confirmatory approach to test the presence of a change point at a given moment. The effectiveness of the methodology was assessed with numerical simulations and NASA's Apollo 13 mission data. The latter revealed dynamic communication behavior and identified time zones where most change points occurred, including around the time of the famous quote “Houston, we've had a problem.”",

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AB - This paper presents an extension to the relational event model with change points (REM-CP) to study abrupt changes to social interaction behavior in temporal networks. A change point detection algorithm is proposed for exploring when and which network effects abruptly change, and a confirmatory approach to test the presence of a change point at a given moment. The effectiveness of the methodology was assessed with numerical simulations and NASA's Apollo 13 mission data. The latter revealed dynamic communication behavior and identified time zones where most change points occurred, including around the time of the famous quote “Houston, we've had a problem.”

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KW - Change point detection

KW - Communication

KW - Critical incident analysis

KW - Critical situation

KW - Graceful extensibility

KW - Relational event model

KW - Resilience engineering

KW - Social network analysis

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JO - Social Networks

JF - Social Networks

ER -

What is the Point of Change? Change Point Detection in Relational Event Models

Abstract

Bibliographical note

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Keywords

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